RJ GIFFORD

Virology | Evolution | Genomics

New frontiers in virus research

Genome sequencing technologies have revolutionised virology.
My research aims to take advantage of these transformative advances
to explore fundamental aspects of virus biology and evolution.

My research is primarily computational, but I also work closely
with doctors, veterinarians, epidemiologists and wet lab-based molecular biologists.
My research cover several related themes, outlined below.

1. Applied virus genomics

1.1. Treatment of hepatitis C virus infection

Hepatitis C virus (HCV) infection is a major cause of chronic liver disease,
and infects >70 million people worldwide. Antiviral drugs can cure HCV infection
but efficacy of treatment varies according to factors associated with genetic variation.
Analysis of genomic data can help
optimise treatment of HCV-infected individuals, and guide the development
of strategies for
eliminating HCV infection
entirely.

To support this, we have developed
HCV-GLUE
- a sequence-based resource for HCV that links a large set of
richly-annotated, highly organised virus genome sequences with information about drug
efficacy.

We are collaborating with CVR investigators
John McLauchlan
and
Emma Thomson,
along with two national HCV research initiatives
(STOP HCV
and
HCV Research UK),
to further develop this resource as a tool supporting clinical decision-making in HCV treatment programmes.

1.2. Surveillance & monitoring of pathogenic viruses

We are developing resources for
bluetongue virus
(BTV) and
rabies virus
(RABV) that are designed to support genomic surveillance and outbreak response
initiatives for these animal pathogens.

For bluetongue virus, we have established the first online database focussed on collating
genomic data:
BTV-GLUE.
Currently, we are working with
Massimo Palmarini
to establish an overview of BTV genetic diversity,
and determine the geographic associations of particular strains.
Through our involvement in
PALE-BLUE
we plan to link BTV-GLUE with a database of BTV isolates held at Pirbright.

For rabies virus, we have established an offline database and fledgling strain-typing tool.
Currently, we are working with
Katie Hampson
and collaborators at
BACHM
to further develop this resource.

1.3. Comparative genomics for experimental virology

Genomic data can inform basic, experimental investigations of virus replication.
Our work in this area
mainly focuses on human immunodeficiency virus type 1 (HIV-1).
We are part of the
Center for HIV RNA Studies (CRNA):
an integrated team of biophysicists, cell and computational biologists,
chemists, and virologists dedicated to understanding the role of RNA in HIV replication.

We have developed sequence-based resources to support the experimental work being
performed on HIV-1 by the CRNA, and by our CVR collaborators
Sam Wilson
and
Suzannah Rihn.

2. Coevolution of viruses and their hosts

2.1. Paleovirology

We make extensive use of endogenous viral elements (EVEs) in our
research. EVEs are DNA sequences derived from ancient viruses (paleoviruses)
that occur in the genomes of eukaryotic organisms.
We have developed a computational approach for exploring the diversity of
EVEs in published genome sequence data, called
database-integrated genome screening
(DIGS).

We organise EVE sequences recovered via DIGS using our software package
GLUE, to expedite
their further use in virological and genomic research.
In our own research, we are exploiting these GLUE-based resources in a variety of ways:

Firstly,
EVE sequences are similar in some ways to 'virus fossils' - they provide unique
retrospective information about extinct viruses and their interactions with ancestral
host species. We use comparative approaches to mine the EVE 'fossil record'
for information about virus ecology and evolution.

Finally, we are using EVE data to examine the impact of horizontal gene transfer from viruses
on the evolution of eukaryotic genomes (see section 2.2. below)

2.2. Impact of viruses on host genomes

The immense selective pressure that viruses have exerted on host species has
left a deep imprint on their genomes.
One aspect of this related to antiviral defence - host species have evolved
an arsenal of antiviral genes that block viral infections.

Also - and in close relation to our 'paleovirological' work (section 2.1 above) - we are
interested in how horizontal transfer of genetic information from virus to host genomes
has impacted evolution. One of the most remarkable things to be revealed by
genomics is the extent to which viruses and transposons have influenced eukaryotic
genome evolution.

In particular, retroviruses have viruses have been motors of genome evolution in mammals.
We are collaborating with
Helen Rowe
at University College London to investigate how epigenetic modulation of
endogenous retroviruses has contributed to the evolution of gene regulatory networks
in mammals.

2.3. Impact of technology on viral emergence

The historical role that technology has played in enabling viral emergence is
a developing theme in our research.

Until fairly recently, it was only
possible to speculate about what drove the emergence of contemporary viral diseases.
However, as more genomic data become available (including some that preserve
retrospective information) we increasingly have the means
to explore these questions.

We have used genetic data to demonstrate a likely role for experimental
malaria studies, and later the development of avian cell culture techniques, in
facilitating the iatrogenic
transmission of a retrovirus to birds.
More recently, we have
been reconstructing the events that enabled pandemic spread of small ruminant
lentiviruses (the sheep and goat equivalents of HIV-1).

3. Software development

3.1. GLUE - a power tool for virus genomics

We have developed
GLUE,
a bioinformatics environment for virus sequence data that
not only
facilitates the implementation
of diverse, data-oriented resources for viruses,
but also
supports the
stable development of these resources as reusable digital assets.

3.2. The DIGS tool - heuristically exploring genome databases

A significant fraction of most genomes is comprised of DNA sequences that have
been incompletely investigated. This genomic ‘dark matter’ contains a wealth of
useful biological information that can be recovered by systematically screening
genomes in silico using sequence similarity search tools. Specialized computational
tools are required to implement these screens efficiently.
The database-integrated genome-screening (DIGS) tool is a computational framework
for performing these
investigations.